6 Things You Need to Know About Digital Data Extraction

In the current ever-growing digital world, data is the lifeline of every business with an online presence. The importance of data is rapidly growing as companies collect more and more information regarding their customers each passing day. The global data extraction market is expected to reach $4.90 billion by 2027, with a probable CAGR growth of 11.8 percent between 2020 and 2027. Yet, data is useful only in its structured and readable form.

The way to benefit from data is by collecting useful business information through analytics. This post explores data extraction, which is the first component in the Extract, Transform, Load (ETL) process, used in data workflows.

6 Things About Digital Data Extraction That You Didn’t Already Know

Data extraction through digital means requires capturing and processing unstructured data to transform it into understandable information. Data entry services often help store and collate data as per requirement, which is one of the ways of saving useful information. Here are six things you must know about digital data extraction:

What is Data Extraction?

In simple and clear terms, data extraction refers to the process of obtaining relevant data from multiple sources, such as a database or a SaaS platform. By leveraging digital data extraction solutions, businesses store, transform, structure, and feed enterprise data into a system. The idea behind it is to analyze and process the data to pull out useful information for business growth. Often, data extraction is also defined as data collection as it involves gathering data from several resources, including emails, websites, Relational Database Management System (RDBMS), documents, Portable Document Format (PDFs), scanned text, and more.

The process of data extraction begins with considering multiple aspects that involves identifying the data sources, the method to extract data, and the reliability to extract data in this particular manner.

Where to Extract Data from?

Businesses might have to extract the data from the following sources:

  • PDFs
  • Technical documents
  • Emails
  • Databases
  • Invoices
  • Spreadsheets
  • RDBMS
  • Websites

Many more information-based sources exist from which a company might need to pull out data for business purposes.

Importance of Data Extraction

The job of digital data extraction is not limited to pulling out information from some documents and collecting them at one central location. Instead, it enables companies to focus more on running the business rather than spend time on manual data entry services, which are often riddled with errors.

Here is why data extraction is an important aspect of any organization:

  • Simplified sharing of data: Data collection from a single unified platform ease up the sharing of information and access with the entire organization.
  • Save time and money: Manual data entry services take up a significant amount of time yet are inefficient and error prone. Additionally, hiring people for data entry jobs is often expensive. Data extraction solutions put an end to both problems.
  • Accurate, structured data for business growth: Today, everything runs on data. Data is the single most important source from training an artificial intelligence system to understanding customer behavior. Digital data extraction solutions offer accurate, structured data that help businesses fulfilll such actions.

Types of Data Extraction

There are typically two types of data extraction: Logical and Physical data extraction.

Logical data extraction: This type is further divided into two types – Full and incremental data extraction. While data is at once pulled out from the source without adding or updating information in full extraction, incremental extraction deals with extracting data by recognizing new or changed information based on time and dates.

Physical data extraction: This extraction type replicates the exact information from the source to the destination, including hidden or deleted files. Physical extraction is of two types: online and offline. Online extraction involves direct data transfer from the source system to the data warehouse. On the other hand, the entire process happens outside the source system in offline extraction, where the data is already structured or organised using extraction routines.

Data Extraction Process

The process to extract data is straightforward. Although there may be other steps involved, the basic structure of the data extraction process involves these stages:

  • Analyze the existing data and changes, including updated dates, added tables, or more. Any addition or deletion to the current data must be dealt with programmatically.
  • Retrieve the data from target documents or tables and fields as per the requirement.
  • Extract the relevant data as per your need.

Digital Data Extraction Solution Tools

You already know that manual data entry services and extraction solutions are inaccurate, expensive, and time-consuming. Hence, using tools for digital data extraction solutions is the best way to pull out information.

Many tools help in the data extraction process, which efficiently and quickly extract data from the source. Additionally, they ensure that any addition or deletion from the source is automatically updated and reflected in the destination. All you must do is hire a service provider to monitor the process and check if the data is structured and ready-to-use. The best part about this approach is, you don’t have to stress about doing it in-house. Instead, you can move your focus to core business functions.

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